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The Customer Data Platform Explained: What is a CDP and Why Should You Use One?

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Modern businesses can collect more data than ever about their customers, but it’s the customer data platform (CDP) that allows them to turn it into actionable insights.

According to McKinsey 71% of consumers now expect personalized, end-to-end customer experiences. The brands that are able to master this gain a tremendous competitive advantage over companies that aren’t effectively leveraging their customer data.

A CDP helps companies implement personalization by unifying relevant consumer data points across tools to create a single customer view, or customer 360. With access to rich, up-to-date information, teams can build strong customer relationships at scale.


Since its formal inception in 2010, the CDP has continued to evolve, and with many different approaches now available, CDP software can seem more complicated than it needs to be. Read on to demystify what a customer data platform is, how it works, and how to choose an effective CDP for your business.

The customer data platform (CDP) was created to help companies build this single customer view. Since its formal inception in 2010, the CDP has evolved significantly and today there are many different CDP approaches. Many innovative companies opt for a modern warehouse native. In this post, we’ll answer all of your questions about CDPs to help you get on the path to mastering personalization.

What is a Customer Data Platform?

As a relatively nascent technology, a CDP definition is best understood when considering the software’s fundamental goal.

So, with that in mind: CDP stands for customer data platform. They exist to help companies drive more business value with their consumer data by building unified customer profile views. They typically perform the three key functions of data collection, data unification, and data activation.

But, what is a customer data platform exactly? Now that we have a broad definition, let’s dig a little deeper into that question.

A CDP is a specialized software platform designed to centralize customer data from various sources, unify that data to build complete customer profiles, and facilitate the activation of those profiles to enrich the quality of customer interactions across multiple touchpoints. The complete customer profile – often called a single customer view or customer 360 – is the central component of the CDP.

Unlike traditional data management tools, a CDP is designed to eliminate data silos by aggregating and organizing data from multiple first and third-party data sources. Once the complete customer profiles are created from this unified data, the CDP makes them available – either within the CDP itself or in downstream systems – for use in delivering personalized messaging, contextualized interactions, and custom experiences.

CDP software enables companies to better understand individual customer behavior, preferences, and interactions to unlock otherwise out-of-reach use cases that drive better business outcomes. This unified view of the customer adds value by:

  • Providing deeper insights into customers via analytics
  • Enriching the quality of customer interactions
  • Pushing customer intelligence to key teams, such as sales, marketing, or customer support
  • Controlling governance and privacy for customer data

While CDPs were initially created for marketing use cases, every business unit can leverage customer data to drive better outcomes. Modern CDPs embrace a “build once, use everywhere” mentality and enable every business unit to take advantage of the CDP’s customer profiles to make sure customer interactions are personalized, consistent across touchpoints, and valuable for all parties involved.

Understanding Why Customer Data Platforms Were Needed

The history of the CDP is best understood when framed by the challenges businesses face in managing customer data.

Customer data comes from many different sources and is typically scattered across various systems and SaaS platforms. These platforms lock data into their own ecosystems, creating numerous data silos and a fragmented landscape. The result of this is that teams will have to work with unsynchronized sources of truth.

In this situation, anything close to a customer 360 is completely out of reach and the leverage a company can create is severely limited. When the teams creating and contributing to the customer experience are operating with a limited picture of the customer journey, opportunities will be missed and experiences will be inconsistent and impersonal.

In contrast, customer 360 serves as a single source of truth for the entire company. According to Gartner, companies that manage to successfully implement a customer 360 benefit from increased operational efficiency, higher customer satisfaction, and higher profitability. They also gain a major competitive advantage over companies that fail to implement a customer 360.

With so much opportunity on the table, there has been much innovation aimed at delivering the promise of customer 360. Tooling first emerged somewhat unintentionally, originating as CRMs, infrastructure tools, databases, or tag managers. Eventually, the CDP was formalized as a SaaS tool created primarily for marketing teams. These legacy CDPs promised to automatically bring in first-party data from various sources, structure it in a consistent format, and create comprehensive customer profiles that could be used for analytical and marketing purposes.

Many of these legacy CDPs also provided orchestration tooling to enable the tactical activation of data for omnichannel customer engagement. For customer-centric marketing teams, this would help ensure a consistent customer experience across web and mobile properties, email, social media, and paid digital advertisements. However, the issue with using a CDP for marketing is that it will still create another data silo. While they will deliver powerful engagement and automation features, they’re still largely closed, black box, systems and there is no easy way for teams outside of marketing to access their valuable metrics.

But, there’s been a paradigm shift, and SaaS tooling is more dynamic today. Innovations around the cloud data warehouse have enabled companies to effectively build CDP software on top of their own data warehouse. David Raab, founder of The CDP Institute, has said: “Modern warehouses, such as Snowflake, use more flexible data stores and can do more things, including much of what would typically be done in a CDP.”

Many innovative companies are now embracing a warehouse native approach to the CDP. In this system, customer data is centralized and unified in the data warehouse. It is then delivered downstream to the tools (including marketing data platforms) that business teams use to drive the customer experience.

What Does a CDP Do?

Now we understand where CDPs came from and the challenges they are intended to overcome. The next question to answer is: ‘How does a CDP work?’ To answer this, we must explore the data activation lifecycle.

The Data Activation Lifecycle

The Three Stages of the Data Activation Lifecycle

  1. Data collection: CDP integrations with first-party data sources capture customer information relevant to an organization. This includes marketing, sales, support, and the product itself.
  2. Data unification: Consumer data is built into customer profiles (also known as Customer 360 or Identity Resolution) that are a combination of static traits as well as aggregate behavior information.
  3. Data activation: Once the profiles are built, internal apps and other systems use the data to personalize communications or contextualize interactions.

Data collection

There are several ways of bringing in data, many of which are understood in the context of the modern data stack. These are the most common examples.

  • Application Event Tracking. Organizations can leverage SDKs across a variety of languages that enable them to track and understand user behavior and flows throughout a software application. This can be done either on the client (Mobile, Web, Smart Device) or on the server (Python, Java, Go, etc.) with trade-offs for each.
  • Vendor Webhooks. Some software vendors expose webhooks on activity that happens on their platform. These data streams are private to the organization using the vendor and provide information on how the vendors are used.
  • Production Databases. Production databases are a good source of truth for application transactions or production data models. These data streams are often brought in via ELT/ETL (extract, transform, load) processes that leverage modern techniques like change data capture (CDC).
  • Vendor Data Extracts. Vendors that directly engage with customers on behalf of an organization often hold the data within their systems. This data can be extracted in batch through vendor provided APIs.

Data Unification

Collecting and centralizing your customer data enables you to build unified, comprehensive customer profiles based on every touchpoint with your organization. Given the data that is collected through upstream integrations, a customer data platform builds a single view of the user that can be understood, filtered, aggregated, or propagated, depending on the use case.

Advanced features in building customer profiles include:

  • Personalization. Machine learning models or simple heuristics can help predict what customers are interested in based on existing interaction. This includes personalized recommendations, personalized messaging, or cohort-specific customer journeys. Here's how one of our customers leverages RudderStack and Redis for real-time personalization.
  • Customer Health. Customer health is based on a combination of engagement (or lack thereof), quality of interaction, direct feedback, and more. This information can help guide messaging that is encouraging, conciliatory, determined or exploratory depending on how the customer feels about the company/product.
  • Identity resolution. Customer interactions across many tools often share an identifier, but pseudo-anonymous interactions (e.g. pre-login) benefit from being stitched back together to customers once you determine who they were. Learn more about identity resolution.

Data Activation

Data activation on a customer data platform involves making it available to downstream communication platforms, whether it be sales, marketing, support, or the product itself. These are often the same tools used to capture these interactions from the “data collection” section above.

This can involve either pushing the downstream systems or exposing an interface (e.g. API endpoint) that enables vendors to access and aggregate customer data. If the data lives in a cloud data warehouse, there may be technological overlap with products in the Reverse ETL category which helps push data from warehouses to downstream integrations.

In addition to using data for individual customers, CDPs enable organizations to build audience lists or identify properties based on features of audiences. For example, if you want to target all customers from Europe who joined in the past five days, a CDP would enable you to leverage the central customer profile to build an audience list that could be used on your communication platforms.

What Data Does a Customer Data Platform Use?

Your CDP can’t create customer profiles without customer data. Building a customer 360, begins with collecting data from every customer touchpoint and augmenting it with available enrichment data. The exact makeup of customer profiles will vary across businesses and industries, and no one knows your specific needs like you do, but it’s helpful to consider the basic building blocks.

First-party data is the most critical data component when it comes to your customer profiles. You should prioritize this as the foundation of your customer 360, but a comprehensive picture of the customer typically includes data from available second and third-party sources. Below, we’ll provide an overview of each data source:

  • First-party user behavior data – Called clickstream or event data, this data gets collected in real-time and represents your customer’s digital customer journey. It includes all of the actions taken by your users across platforms and devices.
  • First-party batch data – Often thought of as traditional ETL data, batch data includes all of the customer information stored in cloud SaaS tools and databases such as your CRM or support desk tool.
  • Second and third-party data – This data can be grouped together and called enrichment data. It augments your first-party data to give you more comprehensive customer profiles. Second-party data might come from ad platforms and shipping/delivery systems while third-party data, purchased from data vendors, can complete your customer picture with browsing, intent, and demo/firmographic data.

What are the business benefits of using a Customer Data Platform?

We’ve already briefly mentioned some of the benefits that businesses can expect from using a CDP. Let’s look at some of those customer data platform advantages in a bit more detail.

  • Customer 360: First and foremost, using CDP features to unify customer data and create a single client view and source of truth allows businesses to increase customer analytics and insights, providing a competitive advantage
  • Improved customer experiences: The improved customer analytics provided by CDPs and customer 360 allow companies to successfully implement personalization, increasing customer satisfaction, loyalty, and conversions.
  • Operational agility: CDPs facilitate the democratization of data by breaking down data silos, creating one source of truth and making data accessible to all departments to increase consistency and collaboration.
  • Stronger compliance: Because CDP software involves proactive management of consumer data, it makes it easier to streamline data governance and meet the straight regulations necessary for gathering consumer data.

How other companies use CDPs

But, what do these customer data platform benefits look like in action? We have three case studies from customers successfully driving better outcomes with the RudderStack Warehouse Native CDP to answer the question of what does a customer data platform do for real-life companies.


Wyze Delivers AI-driven Campaigns With RudderStack Profiles and Snowflake – Wyze is now delivering 3x more ML-driven marketing campaigns with RudderStack thanks to a more efficient data function. With data collection and unification solved, data engineering increased productivity 10x. Similarly, the AI team’s productivity has tripled because they’re getting better data to start with, and it’s easier for them to quickly define new features.

RudderStack’s warehouse native approach eliminated the manual processes bogging down our data engineers. With clean data at their disposal and automated workflows to route it downstream, they started providing our AI/ML, marketing, and product teams with actionable information to drive new models and power new processes.

Wei Zhou, Director of Data Engineering at Wyze
  • Joybird overcomes data integration challenges – Joybird streamlined data collection and activation with RudderStack, enabling marketing to spin up new, personalized campaigns with valuable data from their Snowflake data warehouse in one hour, a process that used to take two weeks.

RudderStack’s warehouse-first approach gives us the best of both worlds. We have the event data streams that we can activate in real-time. We also send the event data to Snowflake and join it with data from different CRM services to create a richer customer profile that we can then send to downstream destinations such as Iterable via Reverse-ETL.

Brett Trani, Director of Analytics at Joybird
  • HealthMatch Builds a Scalable HIPAA-Compliant Tech Stack – Healthmatch created a new customer engagement workflow and unlocked full customer journey analytics with RudderStack. Best of all, because of our Warehouse Native approach they did it with a fully HIPAA-compliant stack.

HealthMatch is a small company with a big idea. We match over one million patients with 300 plus medical conditions with clinical trial sponsors and researchers in four countries. Despite our vision, we were hampered by our limited technology stack comprising SendGrid and Google Analytics. Over seven days, we built a full-blown customer engagement system using Customer.io and RudderStack.

HealthMatch Product Lead, Joel Pinkham

Choosing the Best Customer Data Platform for Your Business

Despite knowing and understanding the customer data platform capabilities, choosing the best CDP software for your business can still be intimidating. Here’s what you need to know.

Understanding the Different Types of Customer Data Platforms

According to the CDP Institute's classification, Customer Data Platforms can be categorized into several distinct types, each with unique CDP features and use focuses. These are the most common types:

  • Data CDPs: These platforms primarily focus on accumulating data from various sources, aligning this data with individual customer profiles, and then making it accessible to other business applications in the form of audience segments. They play a crucial role in ensuring that customer data is effectively captured and organized for further use.
  • Analytics CDPs: Going beyond data collection and assembly, these platforms add advanced CDP features, such as machine learning, customer journey mapping, predictive modeling, and revenue attribution, to enhance their functionality. Analytics CDPs are integral in deriving deeper insights from customer data, enabling businesses to make more informed decisions.
  • Campaign CDPs: Specializing in segmentation, Campaign CDPs focus on analytics and specific customer treatments. They are instrumental in orchestrating customer interactions across various marketing channels. This includes personalized messaging, outbound marketing campaigns, real-time interactions, and tailored recommendations, ensuring a cohesive and customized marketing approach.
  • Delivery CDPs: While encompassing all the standard capabilities of a traditional CDP, Delivery CDPs specialize in the distribution of messaging through various channels such as email, websites, mobile apps, advertising platforms, and CRMs. This specialization allows for a targeted and efficient communication strategy.

Top Tips for Selecting a CDP

The best customer data platform for you depends on a number of factors you may value for your business, for example, data storage, privacy, control, cost, completeness, extensibility, and more. Here are a few considerations that should inform your CDP evaluation:

  • How complete is the data coming in? With the new wave of privacy-conscious browser restrictions designed to improve user privacy and weaken the marketplace of data brokers, first-party event collection systems are often affected even though they are not the intended target. Effective CDPs have a number of approaches to tackling external challenges and verifying data quality.
  • How good is the data coming in? Do you need tight controls over the quality of data coming in from your application, vendors, and databases? Some CDPs support the concept of Tracking Plans to verify that data coming in has a consistent format that can be used to accurately update a user profile.
  • How much control do you have over your data? When working with a customer data platform, do you need to interact with the data directly, or are you ok working with the data through interfaces provided by the CDP? If a CDP shares its data with you or lives on a cloud data warehouse, then you have more visibility into your data and can re-use your customer data profiles for custom processing and analytics, giving you more data control.
  • What channels do you use to communicate with customers? B2B organizations have high-value investments in a smaller number of customers through sales processes, while B2C (such as ecommerce or marketplaces) organizations traditionally invest more in digital marketing and advertisements. Different CDPs have product optimizations or cost models that may be more advantageous for one or the other.
  • How comprehensive is your data privacy program? Data privacy laws such as GDPR and CCPA put stricter controls on the collection, access, storage, and facilitation of customer data. Your CDP can play a significant role in your data privacy by providing compliance for data within its system as well as the forward deletion requests to downstream systems. In addition to this, some CDPs may go one step further with compliance for medical data (HIPAA).

CDP Business Rationale: Should You Build or Buy?

The underlying goal for most businesses implementing a CDP is to improve their customers’ experience. While such an improvement sounds straightforward, it’s anything but for large businesses with thousands of employees and numerous stakeholders involved in business decisions.

Soumyadeb Mitra, RudderStack’s CEO, goes into the details of how to address this challenge in the post Build or Buy? Lessons From Ten Years Building Customer Data Pipelines.

In short, to give the right teams the necessary information about what needs to be changed to improve customer experience, the following steps are needed:

  1. Collect information about each interaction a customer has with your business.
  2. Unify that data and store it in a centralized location.
  3. Enrich the data and integrate it into other tools used by product, development, marketing, and sales teams.

Once the decision is made on implementing a CDP, there is another important decision to make: should you build your own CDP, or should you implement a third-party product instead?

For those choosing to build, the common challenges include:

  • Scaling the infrastructure to support millions of events per day and more
  • Integrating the CDP with all the necessary data sources, such as databases, other SaaS products, and advertising platforms like Google Ads
  • Transforming the data into a standardized format and ensuring the data is being updated correctly with new events
  • Dealing with privacy regulations that affect customer data
  • Being able to support internal demand for new functionality or CDP integrations, while maintaining existing ones (e.g. changes in destination API versions, deprecated endpoints, etc.)

Those buying a third-party solution will likely run into issues like:

  • Data lock-in: inability to fully leverage the data you collect because of how and where it’s stored by the vendor’s product
  • Lack of customization options and support for complex use cases
  • High cost, especially for vendors that both process and store your data
  • High cost of switching: Since CDP data collection and destinations are often core to supporting business processes, replacing such a core component of your business requires significant planning and resources
  • Potential regulatory requirements: If you cannot send, store, or process your data outside your own infrastructure, certain types of CDPs may not even be an option in the first place

The challenges of building your own CDP are highly complex, and using third-party software can be a way to avoid the headache of self-building. It’s worth considering whether you have the resources to build your own CDP, as well as evaluating the cost of any third-party software and the level of control you will have over it, before making a decision.

Build a world-class customer experience with the Warehouse Native CDP

The Superior CDP Architecture of RudderStack's Warehouse Native Approach

Rudderstack offers CDP software that actively addresses the common challenges of third-party customer data platform solutions through our unique warehouse native product. It’s unavoidable that if you want to solve issues around data integration, build truly comprehensive customer profiles, and enable every team in your organization to successfully use them to drive better outcomes, you need to use a CDP. So, why not use the best?

No matter where you are on your data maturity journey, RudderStack can help you collect comprehensive data about your customers and use it to make an impact.


You can also learn more about customer data in our corpus of related articles, including:

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December 15, 2023
Matthew Sibun

Matthew Sibun

Head of Growth Marketing

Brooks Patterson

Brooks Patterson

Product Marketing Manager